Search results for: linear and polynomial model
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 18764

Search results for: linear and polynomial model

16754 Research on Configuration of Large-Scale Linear Array Feeder Truss Parabolic Cylindrical Antenna of Satellite

Authors: Chen Chuanzhi, Guo Yunyun

Abstract:

The large linear array feeding parabolic cylindrical antenna of the satellite has the ability of large-area line focusing, multi-directional beam clusters simultaneously in a certain azimuth plane and elevation plane, corresponding quickly to different orientations and different directions in a wide frequency range, dual aiming of frequency and direction, and combining space power. Therefore, the large-diameter parabolic cylindrical antenna has become one of the new development directions of spaceborne antennas. Limited by the size of the rocked fairing, the large-diameter spaceborne antenna is required to be small mass and have a deployment function. After being orbited, the antenna can be deployed by expanding and be stabilized. However, few types of structures can be used to construct large cylindrical shell structures in existing structures, which greatly limits the development and application of such antennas. Aiming at high structural efficiency, the geometrical characteristics of parabolic cylinders and mechanism topological mapping law to the expandable truss are studied, and the basic configuration of deployable truss with cylindrical shell is structured. Then a modular truss parabolic cylindrical antenna is designed in this paper. The antenna has the characteristics of stable structure, high precision of reflecting surface formation, controllable motion process, high storage rate, and lightweight, etc. On the basis of the overall configuration comprehensive theory and optimization method, the structural stiffness of the modular truss parabolic cylindrical antenna is improved. And the bearing density and impact resistance of support structure are improved based on the internal tension optimal distribution method of reflector forming. Finally, a truss-type cylindrical deployable support structure with high constriction-deployment ratio, high stiffness, controllable deployment, and low mass is successfully developed, laying the foundation for the application of large-diameter parabolic cylindrical antennas in satellite antennas.

Keywords: linear array feed antenna, truss type, parabolic cylindrical antenna, spaceborne antenna

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16753 Formal Group Laws and Toposes in Gauge Theory

Authors: Patrascu Andrei Tudor

Abstract:

One of the main problems in high energy physics is the fact that we do not have a complete understanding of the interaction between local and global effects in gauge theory. This has an increasing impact on our ability to access the non-perturbative regime of most of our theories. Our theories, while being based on gauge groups considered to be simple or semi-simple and connected, are expected to be described by their simple local linear approximation, namely the Lie algebras. However, higher homotopy properties resulting in gauge anomalies appear frequently in theories of physical interest. Our assumption that the groups we deal with are simple and simply connected is probably not suitable, and ways to go beyond such assumptions, particularly in gauge theories, where the Lie algebra linear approximation is prevalent, are not known. We approach this problem from two directions: on one side we are explaining the potential role of formal group laws in describing certain higher homotopical properties and interferences with local or perturbative effects, and on the other side, we employ a categorical approach leading to synthetic theory and a way of looking at gauge theories. The topos approach is based on a geometry where the fundamental logic is intuitionistic logic, and hence the ‘tertium non datur’ principle is abandoned. This has a remarkable impact on understanding conformal symmetry and its anomalies in string theory in various dimensions.

Keywords: Gauge theory, formal group laws, Topos theory, conformal symmetry

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16752 Bird-Adapted Filter for Avian Species and Individual Identification Systems Improvement

Authors: Ladislav Ptacek, Jan Vanek, Jan Eisner, Alexandra Pruchova, Pavel Linhart, Ludek Muller, Dana Jirotkova

Abstract:

One of the essential steps of avian song processing is signal filtering. Currently, the standard methods of filtering are the Mel Bank Filter or linear filter distribution. In this article, a new type of bank filter called the Bird-Adapted Filter is introduced; whereby the signal filtering is modifiable, based upon a new mathematical description of audiograms for particular bird species or order, which was named the Avian Audiogram Unified Equation. According to the method, filters may be deliberately distributed by frequency. The filters are more concentrated in bands of higher sensitivity where there is expected to be more information transmitted and vice versa. Further, it is demonstrated a comparison of various filters for automatic individual recognition of chiffchaff (Phylloscopus collybita). The average Equal Error Rate (EER) value for Linear bank filter was 16.23%, for Mel Bank Filter 18.71%, the Bird-Adapted Filter gave 14.29%, and Bird-Adapted Filter with 1/3 modification was 12.95%. This approach would be useful for practical use in automatic systems for avian species and individual identification. Since the Bird-Adapted Filter filtration is based on the measured audiograms of particular species or orders, selecting the distribution according to the avian vocalization provides the most precise filter distribution to date.

Keywords: avian audiogram, bird individual identification, bird song processing, bird species recognition, filter bank

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16751 Resolution and Experimental Validation of the Asymptotic Model of a Viscous Laminar Supersonic Flow around a Thin Airfoil

Authors: Eddegdag Nasser, Naamane Azzeddine, Radouani Mohammed, Ensam Meknes

Abstract:

In this study, we are interested in the asymptotic modeling of the two-dimensional stationary supersonic flow of a viscous compressible fluid around wing airfoil. The aim of this article is to solve the partial differential equations of the flow far from the leading edge and near the wall using the triple-deck technique is what brought again in precision according to the principle of least degeneration. In order to validate our theoretical model, these obtained results will be compared with the experimental results. The comparison of the results of our model with experimentation has shown that they are quantitatively acceptable compared to the obtained experimental results. The experimental study was conducted using the AF300 supersonic wind tunnel and a NACA Reduced airfoil model with two pressure Taps on extrados. In this experiment, we have considered the incident upstream supersonic Mach number over a dissymmetric NACA airfoil wing. The validation and the accuracy of the results support our model.

Keywords: supersonic, viscous, triple deck technique, asymptotic methods, AF300 supersonic wind tunnel, reduced airfoil model

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16750 Stability Analysis for an Extended Model of the Hypothalamus-Pituitary-Thyroid Axis

Authors: Beata Jackowska-Zduniak

Abstract:

We formulate and analyze a mathematical model describing dynamics of the hypothalamus-pituitary-thyroid homoeostatic mechanism in endocrine system. We introduce to this system two types of couplings and delay. In our model, feedback controls the secretion of thyroid hormones and delay reflects time lags required for transportation of the hormones. The influence of delayed feedback on the stability behaviour of the system is discussed. Analytical results are illustrated by numerical examples of the model dynamics. This system of equations describes normal activity of the thyroid and also a couple of types of malfunctions (e.g. hyperthyroidism).

Keywords: mathematical modeling, ordinary differential equations, endocrine system, delay differential equation

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16749 Safe and Efficient Deep Reinforcement Learning Control Model: A Hydroponics Case Study

Authors: Almutasim Billa A. Alanazi, Hal S. Tharp

Abstract:

Safe performance and efficient energy consumption are essential factors for designing a control system. This paper presents a reinforcement learning (RL) model that can be applied to control applications to improve safety and reduce energy consumption. As hardware constraints and environmental disturbances are imprecise and unpredictable, conventional control methods may not always be effective in optimizing control designs. However, RL has demonstrated its value in several artificial intelligence (AI) applications, especially in the field of control systems. The proposed model intelligently monitors a system's success by observing the rewards from the environment, with positive rewards counting as a success when the controlled reference is within the desired operating zone. Thus, the model can determine whether the system is safe to continue operating based on the designer/user specifications, which can be adjusted as needed. Additionally, the controller keeps track of energy consumption to improve energy efficiency by enabling the idle mode when the controlled reference is within the desired operating zone, thus reducing the system energy consumption during the controlling operation. Water temperature control for a hydroponic system is taken as a case study for the RL model, adjusting the variance of disturbances to show the model’s robustness and efficiency. On average, the model showed safety improvement by up to 15% and energy efficiency improvements by 35%- 40% compared to a traditional RL model.

Keywords: control system, hydroponics, machine learning, reinforcement learning

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16748 Prediction of Coronary Heart Disease Using Fuzzy Logic

Authors: Elda Maraj, Shkelqim Kuka

Abstract:

Coronary heart disease causes many deaths in the world. Unfortunately, this problem will continue to increase in the future. In this paper, a fuzzy logic model to predict coronary heart disease is presented. This model has been developed with seven input variables and one output variable that was implemented for 30 patients in Albania. Here fuzzy logic toolbox of MATLAB is used. Fuzzy model inputs are considered as cholesterol, blood pressure, physical activity, age, BMI, smoking, and diabetes, whereas the output is the disease classification. The fuzzy sets and membership functions are chosen in an appropriate manner. Centroid method is used for defuzzification. The database is taken from University Hospital Center "Mother Teresa" in Tirana, Albania.

Keywords: coronary heart disease, fuzzy logic toolbox, membership function, prediction model

Procedia PDF Downloads 155
16747 A Boundary Fitted Nested Grid Model for Tsunami Computation along Penang Island in Peninsular Malaysia

Authors: Md. Fazlul Karim, Ahmad Izani Md. Ismail, Mohammed Ashaque Meah

Abstract:

This paper focuses on the development of a 2-D Boundary Fitted and Nested Grid (BFNG) model to compute the tsunami propagation of Indonesian tsunami 2004 along the coastal region of Penang in Peninsular Malaysia. In the presence of a curvilinear coastline, boundary fitted grids are suitable to represent the model boundaries accurately. On the other hand, when large gradient of velocity within a confined area is expected, the use of a nested grid system is appropriate to improve the numerical accuracy with the least grid numbers. This paper constructs a shallow water nested and orthogonal boundary fitted grid model and presents computational results of the tsunami impact on the Penang coast due to the Indonesian tsunami of 2004. The results of the numerical simulations are compared with available data.

Keywords: boundary fitted nested model, tsunami, Penang Island, 2004 Indonesian Tsunami

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16746 The Status of BIM Adoption in Six Continents

Authors: Wooyoung Jung, Ghang Lee

Abstract:

This paper paper reports the worldwide status of building information modeling (BIM) adoption from the perspectives of the engagement level, the Hype Cycle model, the technology diffusion model, and BIM-uses. An online survey was distributed, and 156 experts from six continents responded. Overall, North America was the most advanced continent, followed by Oceania and Europe. Countries in Asia perceived their phase mainly as slope of enlightenment (mature) in the Hype Cycle model. In the technology diffusion model, the main BIM-users worldwide were “early majority” (third phase), but those in the Middle East/Africa and South America were “early adopters” (second phase). In addition, the more advanced the country, the more number of BIM services employed in general. In summary, North America, Europe, Oceania, and Asia were advancing rapidly toward the mature stage of BIM, whereas the Middle East/Africa and South America were still in the early phase. The simple indexes used in this study may be used to track the worldwide status of BIM adoption in long-term surveys.

Keywords: BIM adoption, BIM services, hype cycle model, technology diffusion model

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16745 Estimation of the Road Traffic Emissions and Dispersion in the Developing Countries Conditions

Authors: Hicham Gourgue, Ahmed Aharoune, Ahmed Ihlal

Abstract:

We present in this work our model of road traffic emissions (line sources) and dispersion of these emissions, named DISPOLSPEM (Dispersion of Poly Sources and Pollutants Emission Model). In its emission part, this model was designed to keep the consistent bottom-up and top-down approaches. It also allows to generate emission inventories from reduced input parameters being adapted to existing conditions in Morocco and in the other developing countries. While several simplifications are made, all the performance of the model results are kept. A further important advantage of the model is that it allows the uncertainty calculation and emission rate uncertainty according to each of the input parameters. In the dispersion part of the model, an improved line source model has been developed, implemented and tested against a reference solution. It provides improvement in accuracy over previous formulas of line source Gaussian plume model, without being too demanding in terms of computational resources. In the case study presented here, the biggest errors were associated with the ends of line source sections; these errors will be canceled by adjacent sections of line sources during the simulation of a road network. In cases where the wind is parallel to the source line, the use of the combination discretized source and analytical line source formulas minimizes remarkably the error. Because this combination is applied only for a small number of wind directions, it should not excessively increase the calculation time.

Keywords: air pollution, dispersion, emissions, line sources, road traffic, urban transport

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16744 A Model to Assist Military Mission Planners in Identifying and Assessing Variables Impacting Food Security

Authors: Lynndee Kemmet

Abstract:

The U.S. military plays an increasing role in supporting political stability efforts, and this includes efforts to prevent the food insecurity that can trigger political and social instability. This paper presents a model that assists military commanders in identifying variables that impact food production and distribution in their areas of operation (AO), in identifying connections between variables and in assessing the impacts of those variables on food production and distribution. Through use of the model, military units can better target their data collection efforts and can categorize and analyze data within the data categorization framework most widely-used by military forces—PMESII-PT (Political, Military, Economic, Infrastructure, Information, Physical Environment and Time). The model provides flexibility of analysis in that commanders can target analysis to be highly focused on a specific PMESII-PT domain or variable or conduct analysis across multiple PMESII-PT domains. The model is also designed to assist commanders in mapping food systems in their AOs and then identifying components of those systems that must be strengthened or protected.

Keywords: food security, food system model, political stability, US Military

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16743 New Segmentation of Piecewise Moving-Average Model by Using Reversible Jump MCMC Algorithm

Authors: Suparman

Abstract:

This paper addresses the problem of the signal segmentation within a Bayesian framework by using reversible jump MCMC algorithm. The signal is modelled by piecewise constant Moving-Average (MA) model where the numbers of segments, the position of change-point, the order and the coefficient of the MA model for each segment are unknown. The reversible jump MCMC algorithm is then used to generate samples distributed according to the joint posterior distribution of the unknown parameters. These samples allow calculating some interesting features of the posterior distribution. The performance of the methodology is illustrated via several simulation results.

Keywords: piecewise, moving-average model, reversible jump MCMC, signal segmentation

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16742 Deep Neural Networks for Restoration of Sky Images Affected by Static and Anisotropic Aberrations

Authors: Constanza A. Barriga, Rafael Bernardi, Amokrane Berdja, Christian D. Guzman

Abstract:

Most image restoration methods in astronomy rely upon probabilistic tools that infer the best solution for a deconvolution problem. They achieve good performances when the point spread function (PSF) is spatially invariable in the image plane. However, this latter condition is not always satisfied with real optical systems. PSF angular variations cannot be evaluated directly from the observations, neither be corrected at a pixel resolution. We have developed a method for the restoration of images affected by static and anisotropic aberrations using deep neural networks that can be directly applied to sky images. The network is trained using simulated sky images corresponding to the T-80 telescope optical system, an 80 cm survey imager at Cerro Tololo (Chile), which are synthesized using a Zernike polynomial representation of the optical system. Once trained, the network can be used directly on sky images, outputting a corrected version of the image, which has a constant and known PSF across its field-of-view. The method was tested with the T-80 telescope, achieving better results than with PSF deconvolution techniques. We present the method and results on this telescope.

Keywords: aberrations, deep neural networks, image restoration, variable point spread function, wide field images

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16741 A Study on Automotive Attack Database and Data Flow Diagram for Concretization of HEAVENS: A Car Security Model

Authors: Se-Han Lee, Kwang-Woo Go, Gwang-Hyun Ahn, Hee-Sung Park, Cheol-Kyu Han, Jun-Bo Shim, Geun-Chul Kang, Hyun-Jung Lee

Abstract:

In recent years, with the advent of smart cars and the expansion of the market, the announcement of 'Adventures in Automotive Networks and Control Units' at the DEFCON21 conference in 2013 revealed that cars are not safe from hacking. As a result, the HEAVENS model considering not only the functional safety of the vehicle but also the security has been suggested. However, the HEAVENS model only presents a simple process, and there are no detailed procedures and activities for each process, making it difficult to apply it to the actual vehicle security vulnerability check. In this paper, we propose an automated attack database that systematically summarizes attack vectors, attack types, and vulnerable vehicle models to prepare for various car hacking attacks, and data flow diagrams that can detect various vulnerabilities and suggest a way to materialize the HEAVENS model.

Keywords: automotive security, HEAVENS, car hacking, security model, information security

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16740 A TgCNN-Based Surrogate Model for Subsurface Oil-Water Phase Flow under Multi-Well Conditions

Authors: Jian Li

Abstract:

The uncertainty quantification and inversion problems of subsurface oil-water phase flow usually require extensive repeated forward calculations for new runs with changed conditions. To reduce the computational time, various forms of surrogate models have been built. Related research shows that deep learning has emerged as an effective surrogate model, while most surrogate models with deep learning are purely data-driven, which always leads to poor robustness and abnormal results. To guarantee the model more consistent with the physical laws, a coupled theory-guided convolutional neural network (TgCNN) based surrogate model is built to facilitate computation efficiency under the premise of satisfactory accuracy. The model is a convolutional neural network based on multi-well reservoir simulation. The core notion of this proposed method is to bridge two separate blocks on top of an overall network. They underlie the TgCNN model in a coupled form, which reflects the coupling nature of pressure and water saturation in the two-phase flow equation. The model is driven by not only labeled data but also scientific theories, including governing equations, stochastic parameterization, boundary, and initial conditions, well conditions, and expert knowledge. The results show that the TgCNN-based surrogate model exhibits satisfactory accuracy and efficiency in subsurface oil-water phase flow under multi-well conditions.

Keywords: coupled theory-guided convolutional neural network, multi-well conditions, surrogate model, subsurface oil-water phase

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16739 Applicability of Linearized Model of Synchronous Generator for Power System Stability Analysis

Authors: J. Ritonja, B. Grcar

Abstract:

For the synchronous generator simulation and analysis and for the power system stabilizer design and synthesis a mathematical model of synchronous generator is needed. The model has to accurately describe dynamics of oscillations, while at the same time has to be transparent enough for an analysis and sufficiently simplified for design of control system. To study the oscillations of the synchronous generator against to the rest of the power system, the model of the synchronous machine connected to an infinite bus through a transmission line having resistance and inductance is needed. In this paper, the linearized reduced order dynamic model of the synchronous generator connected to the infinite bus is presented and analysed in details. This model accurately describes dynamics of the synchronous generator only in a small vicinity of an equilibrium state. With the digression from the selected equilibrium point the accuracy of this model is decreasing considerably. In this paper, the equations’ descriptions and the parameters’ determinations for the linearized reduced order mathematical model of the synchronous generator are explained and summarized and represent the useful origin for works in the areas of synchronous generators’ dynamic behaviour analysis and synchronous generator’s control systems design and synthesis. The main contribution of this paper represents the detailed analysis of the accuracy of the linearized reduced order dynamic model in the entire synchronous generator’s operating range. Borders of the areas where the linearized reduced order mathematical model represents accurate description of the synchronous generator’s dynamics are determined with the systemic numerical analysis. The thorough eigenvalue analysis of the linearized models in the entire operating range is performed. In the paper, the parameters of the linearized reduced order dynamic model of the laboratory salient poles synchronous generator were determined and used for the analysis. The theoretical conclusions were confirmed with the agreement of experimental and simulation results.

Keywords: eigenvalue analysis, mathematical model, power system stability, synchronous generator

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16738 Diesel Fault Prediction Based on Optimized Gray Neural Network

Authors: Han Bing, Yin Zhenjie

Abstract:

In order to analyze the status of a diesel engine, as well as conduct fault prediction, a new prediction model based on a gray system is proposed in this paper, which takes advantage of the neural network and the genetic algorithm. The proposed GBPGA prediction model builds on the GM (1.5) model and uses a neural network, which is optimized by a genetic algorithm to construct the error compensator. We verify our proposed model on the diesel faulty simulation data and the experimental results show that GBPGA has the potential to employ fault prediction on diesel.

Keywords: fault prediction, neural network, GM(1, 5) genetic algorithm, GBPGA

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16737 Further Investigation of α+12C and α+16O Elastic Scattering

Authors: Sh. Hamada

Abstract:

The current work aims to study the rainbow like-structure observed in the elastic scattering of alpha particles on both 12C and 16O nuclei. We reanalyzed the experimental elastic scattering angular distributions data for α+12C and α+16O nuclear systems at different energies using both optical model and double folding potential of different interaction models such as: CDM3Y1, DDM3Y1, CDM3Y6 and BDM3Y1. Potential created by BDM3Y1 interaction model has the shallowest depth which reflects the necessity to use higher renormalization factor (Nr). Both optical model and double folding potential of different interaction models fairly reproduce the experimental data.

Keywords: density distribution, double folding, elastic scattering, nuclear rainbow, optical model

Procedia PDF Downloads 233
16736 Computational Model of Human Cardiopulmonary System

Authors: Julian Thrash, Douglas Folk, Michael Ciracy, Audrey C. Tseng, Kristen M. Stromsodt, Amber Younggren, Christopher Maciolek

Abstract:

The cardiopulmonary system is comprised of the heart, lungs, and many dynamic feedback mechanisms that control its function based on a multitude of variables. The next generation of cardiopulmonary medical devices will involve adaptive control and smart pacing techniques. However, testing these smart devices on living systems may be unethical and exceedingly expensive. As a solution, a comprehensive computational model of the cardiopulmonary system was implemented in Simulink. The model contains over 240 state variables and over 100 equations previously described in a series of published articles. Simulink was chosen because of its ease of introducing machine learning elements. Initial results indicate that physiologically correct waveforms of pressures and volumes were obtained in the simulation. With the development of a comprehensive computational model, we hope to pioneer the future of predictive medicine by applying our research towards the initial stages of smart devices. After validation, we will introduce and train reinforcement learning agents using the cardiopulmonary model to assist in adaptive control system design. With our cardiopulmonary model, we will accelerate the design and testing of smart and adaptive medical devices to better serve those with cardiovascular disease.

Keywords: adaptive control, cardiopulmonary, computational model, machine learning, predictive medicine

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16735 Functional Instruction Set Simulator (ISS) of a Neural Network (NN) IP with Native BF-16 Generator

Authors: Debajyoti Mukherjee, Arathy B. S., Arpita Sahu, Saranga P. Pogula

Abstract:

A Functional Model to mimic the functional correctness of a Neural Network Compute Accelerator IP is very crucial for design validation. Neural network workloads are based on a Brain Floating Point (BF-16) data type. The major challenge we were facing was the incompatibility of gcc compilers to BF-16 datatype, which we addressed with a native BF-16 generator integrated to our functional model. Moreover, working with big GEMM (General Matrix Multiplication) or SpMM (Sparse Matrix Multiplication) Work Loads (Dense or Sparse) and debugging the failures related to data integrity is highly painstaking. In this paper, we are addressing the quality challenge of such a complex Neural Network Accelerator design by proposing a Functional Model-based scoreboard or Software model using SystemC. The proposed Functional Model executes the assembly code based on the ISA of the processor IP, decodes all instructions, and executes as expected to be done by the DUT. The said model would give a lot of visibility and debug capability in the DUT bringing up micro-steps of execution.

Keywords: ISA (instruction set architecture), NN (neural network), TLM (transaction-level modeling), GEMM (general matrix multiplication)

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16734 Prediction of Bubbly Plume Characteristics Using the Self-Similarity Model

Authors: Li Chen, Alex Skvortsov, Chris Norwood

Abstract:

Gas releasing into water can be found in for many industrial situations. This process results in the formation of bubbles and acoustic emission which depends upon the bubble characteristics. If the bubble creation rates (bubble volume flow rate) are of interest, an inverse method has to be used based on the measurement of acoustic emission. However, there will be sound attenuation through the bubbly plume which will influence the measurement and should be taken into consideration in the model. The sound transmission through the bubbly plume depends on the characteristics of the bubbly plume, such as the shape and the bubble distributions. In this study, the bubbly plume shape is modelled using a self-similarity model, which has been normally applied for a single phase buoyant plume. The prediction is compared with the experimental data. It has been found the model can be applied to a buoyant plume of gas-liquid mixture. The influence of the gas flow rate and discharge nozzle size is studied.

Keywords: bubbly plume, buoyant plume, bubble acoustics, self-similarity model

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16733 End-to-End Spanish-English Sequence Learning Translation Model

Authors: Vidhu Mitha Goutham, Ruma Mukherjee

Abstract:

The low availability of well-trained, unlimited, dynamic-access models for specific languages makes it hard for corporate users to adopt quick translation techniques and incorporate them into product solutions. As translation tasks increasingly require a dynamic sequence learning curve; stable, cost-free opensource models are scarce. We survey and compare current translation techniques and propose a modified sequence to sequence model repurposed with attention techniques. Sequence learning using an encoder-decoder model is now paving the path for higher precision levels in translation. Using a Convolutional Neural Network (CNN) encoder and a Recurrent Neural Network (RNN) decoder background, we use Fairseq tools to produce an end-to-end bilingually trained Spanish-English machine translation model including source language detection. We acquire competitive results using a duo-lingo-corpus trained model to provide for prospective, ready-made plug-in use for compound sentences and document translations. Our model serves a decent system for large, organizational data translation needs. While acknowledging its shortcomings and future scope, it also identifies itself as a well-optimized deep neural network model and solution.

Keywords: attention, encoder-decoder, Fairseq, Seq2Seq, Spanish, translation

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16732 An Investigation about the Health-Promoting Lifestyle of 1389 Emergency Nurses in China

Authors: Lei Ye, Min Liu, Yong-Li Gao, Jun Zhang

Abstract:

Purpose: The aims of the study are to investigate the status of health-promoting lifestyle and to compare the healthy lifestyle of emergency nurses in different levels of hospitals in Sichuan province, China. The investigation is mainly about the health-promoting lifestyle, including spiritual growth, health responsibility, physical activity, nutrition, interpersonal relations, stress management. Then the factors were analyzed influencing the health-promoting lifestyle of emergency nurses in hospitals of Sichuan province in order to find the relevant models to provide reference evidence for intervention. Study Design: A cross-sectional research method was adopted. Stratified cluster sampling, based on geographical location, was used to select the health facilities of 1389 emergency nurses in 54 hospitals from Sichuan province in China. Method: The 52-item, six-factor structure Health-Promoting Lifestyle Profile II (HPLP- II) instrument was used to explore participants’ self-reported health-promoting behaviors and measure the dimensions of health responsibility, physical activity, nutrition, interpersonal relations, spiritual growth, and stress management. Demographic characteristics, education, work duration, emergency nursing work duration and self-rated health status were documented. Analysis: Data were analyzed through SPSS software ver. 17.0. Frequency, percentage, mean ± standard deviation were used to describe the general information, while the Nonparametric Test was used to compare the constituent ratio of general data of different hospitals. One-way ANOVA was used to compare the scores of health-promoting lifestyle in different levels hospital. A multiple linear regression model was established. P values which were less than 0.05 determined statistical significance in all analyses. Result: The survey showed that the total score of health-promoting lifestyle of nurses at emergency departments in Sichuan Province was 120.49 ± 21.280. The relevant dimensions are ranked by scores in descending order: interpersonal relations, nutrition, health responsibility, physical activity, stress management, spiritual growth. The total scores of the three-A hospital were the highest (121.63 ± 0.724), followed by the senior class hospital (119.7 ± 1.362) and three-B hospital (117.80 ± 1.255). The difference was statistically significant (P=0.024). The general data of nurses was used as the independent variable which includes age, gender, marital status, living conditions, nursing income, hospital level, Length of Service in nursing, Length of Service in emergency, Professional Title, education background, and the average number of night shifts. The total score of health-promoting lifestyle was used as dependent variable; Multiple linear regression analysis method was adopted to establish the regression model. The regression equation F = 20.728, R2 = 0.061, P < 0.05, the age, gender, nursing income, turnover intention and status of coping stress affect the health-promoting lifestyle of nurses in emergency department, the result was statistically significant (P < 0.05 ). Conclusion: The results of the investigation indicate that it will help to develop health promoting interventions for emergency nurses in all levels of hospital in Sichuan Province through further research. Managers need to pay more attention to emergency nurses’ exercise, stress management, self-realization, and conduct intervention in nurse training programs.

Keywords: emergency nurse, health-promoting lifestyle profile II, health behaviors, lifestyle

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16731 Effects of pH, Load Capacity and Contact Time in the Sulphate Sorption onto a Functionalized Mesoporous Structure

Authors: Jaime Pizarro, Ximena Castillo

Abstract:

The intensive use of water in agriculture, industry, human consumption and increasing pollution are factors that reduce the availability of water for future generations; the challenge is to advance in sustainable and low-cost solutions to reuse water and to facilitate the availability of the resource in quality and quantity. The use of new low-cost materials with sorbent capacity for pollutants is a solution that contributes to the improvement and expansion of water treatment and reuse systems. Fly ash, a residue from the combustion of coal in power plants that is produced in large quantities in newly industrialized countries, contains a high amount of silicon oxides and aluminum oxides, whose properties can be used for the synthesis of mesoporous materials. Properly functionalized, this material allows obtaining matrixes with high sorption capacity. The mesoporous materials have a large surface area, thermal and mechanical stability, uniform porous structure, and high sorption and functionalization capacities. The goal of this study was to develop hexagonal mesoporous siliceous material (HMS) for the adsorption of sulphate from industrial and mining waters. The silica was extracted from fly ash after calcination at 850 ° C, followed by the addition of water. The mesoporous structure has a surface area of 282 m2 g-1 and a size of 5.7 nm and was functionalized with ethylene diamine through of a self-assembly method. The material was characterized by Diffuse Reflectance Infrared Fourier Transform Spectroscopy (DRIFTS). The capacity of sulphate sorption was evaluated according to pH, maximum load capacity and contact time. The sulphate maximum adsorption capacity was 146.1 mg g-1, which is three times higher than commercial sorbents. The kinetic data were fitted according to a pseudo-second order model with a high coefficient of linear regression at different initial concentrations. The adsorption isotherm that best fitted the experimental data was the Freundlich model.

Keywords: fly ash, mesoporous siliceous, sorption, sulphate

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16730 Interoperable Design Coordination Method for Sharing Communication Information Using Building Information Model Collaboration Format

Authors: Jin Gang Lee, Hyun-Soo Lee, Moonseo Park

Abstract:

The utilization of BIM and IFC allows project participants to collaborate across different areas by consistently sharing interoperable product information represented in a model. Comments or markups generated during the coordination process can be categorized as communication information, which can be shared in less standardized manner. It can be difficult to manage and reuse such information compared to the product information in a model. The present study proposes an interoperable coordination method using BCF (the BIM Collaboration Format) for managing and sharing the communication information during BIM based coordination process. A management function for coordination in the BIM collaboration system is developed to assess its ability to share the communication information in BIM collaboration projects. This approach systematically links communication information during the coordination process to the building model and serves as a type of storage system for retrieving knowledge created during BIM collaboration projects.

Keywords: design coordination, building information model, BIM collaboration format, industry foundation classes

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16729 Impact of Relaxing Incisions on Maxillofacial Growth Following Sommerlad–Furlow Modified Technique in Patients with Isolated Cleft Palate: A Preliminary Comparative Study

Authors: Sadam Elayah, Yang Li, Bing Shi

Abstract:

Background: The impact of relaxing incisions on maxillofacial growth during palatoplasty remains a topic of debate, and further research is needed to understand its effects fully. Thus, the current study is the first long-term study that aimed to assess the maxillofacial growth of patients with isolated cleft palate following the Sommerlad-Furlow modified (S.F) technique and to estimate the impact of relaxing incisions on maxillofacial growth following S.F technique in patients with isolated cleft palate. Methods: A total of 85 participants, 55 patients with non-syndromic isolated soft and hard cleft palate underwent primary palatoplasty with our technique (30 patients received the Sommerlad-Furlow modified technique without relaxing incision (S.F+RI group), and 25 received Sommerlad-Furlow modified technique without relaxing (S.F-RI group) with no significant difference found between them regarding the cleft type, cleft width, and age at repair. While the other 30 were normal participants with skeletal class I pattern (C group). The control group was matched with the study group in number, age, and sex. All the study variables were measured using stable landmarks, including 12 linear and 10 angular variants. Results: The mean ages at collection of cephalograms were 6.03±0.80 in the S.F+RI group, 5.96±0.76 in the S.F-RI group, and 5.91±0.87 in the C group. Regarding cranial base, the results showed no statistically significant differences between the three groups in S-N and S-N-Ba. The S.F+R.I group had a significantly shorter S-Ba than the S.F-R.I & C groups (P= 0.01). However, there was no statistically significant difference between the S.F-R.I & C groups (P=0.80). Regarding the skeletal maxilla, there was no significant difference between the S.F+R.I and S.F-R.I groups in all linear measurements (N-ANS, S- PM & SN-PP ) except Co-A, the S.F+R.I group had significantly shorter Co-A than the S.F-R.I & C groups (P= <0.01). While the angular measurement, S.F+R.I group had significantly less SNA angle than the S.F-R.I & C groups (P= <0.01). Regarding mandibular bone, there were no statistically significant differences in all linear and angular mandibular measurements between the S.F+R.I and S.F-R.I groups. Regarding intermaxillary relation, the S.F+R.I group had significant differences in Co-Gn - Co-A and ANB compared to the S.F-R.I & C groups (P= <0.01). There was no statistically significant difference in PP-MP among the three groups. Conclusion: As a preliminary report, the Sommerlad-Furlow modified technique without relaxing incisions was found to have good maxillary positioning in the face and a satisfactory intermaxillary relationship compared to the Sommerlad-Furlow modified technique with relaxing incisions.

Keywords: relaxing incisions, cleft palate, palatoplasty, maxillofacial growth

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16728 Analysis of the Contribution of Drude and Brendel Model Terms to the Dielectric Function

Authors: Christopher Mkirema Maghanga, Maurice Mghendi Mwamburi

Abstract:

Parametric modeling provides a means to deeper understand the properties of materials. Drude, Brendel, Lorentz and OJL incorporated in SCOUT® software are some of the models used to study dielectric films. In our work, we utilized Brendel and Drude models to extract the optical constants from spectroscopic data of fabricated undoped and niobium doped titanium oxide thin films. The individual contributions by the two models were studied to establish how they influence the dielectric function. The effect of dopants on their influences was also analyzed. For the undoped films, results indicate minimal contribution from the Drude term due to the dielectric nature of the films. However as doping levels increase, the rise in the concentration of free electrons favors the use of Drude model. Brendel model was confirmed to work well with dielectric films - the undoped titanium Oxide films in our case.

Keywords: modeling, Brendel model, optical constants, titanium oxide, Drude Model

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16727 A Multicriteria Mathematical Programming Model for Farm Planning in Greece

Authors: Basil Manos, Parthena Chatzinikolaou, Fedra Kiomourtzi

Abstract:

This paper presents a Multicriteria Mathematical Programming model for farm planning and sustainable optimization of agricultural production. The model can be used as a tool for the analysis and simulation of agricultural production plans, as well as for the study of impacts of various measures of Common Agriculture Policy in the member states of European Union. The model can achieve the optimum production plan of a farm or an agricultural region combining in one utility function different conflicting criteria as the maximization of gross margin and the minimization of fertilizers used, under a set of constraints for land, labor, available capital, Common Agricultural Policy etc. The proposed model was applied to the region of Larisa in central Greece. The optimum production plan achieves a greater gross return, a less fertilizers use, and a less irrigated water use than the existent production plan.

Keywords: sustainable optimization, multicriteria analysis, agricultural production, farm planning

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16726 A Comparative Analysis of E-Government Quality Models

Authors: Abdoullah Fath-Allah, Laila Cheikhi, Rafa E. Al-Qutaish, Ali Idri

Abstract:

Many quality models have been used to measure e-government portals quality. However, the absence of an international consensus for e-government portals quality models results in many differences in terms of quality attributes and measures. The aim of this paper is to compare and analyze the existing e-government quality models proposed in literature (those that are based on ISO standards and those that are not) in order to propose guidelines to build a good and useful e-government portals quality model. Our findings show that, there is no e-government portal quality model based on the new international standard ISO 25010. Besides that, the quality models are not based on a best practice model to allow agencies to both; measure e-government portals quality and identify missing best practices for those portals.

Keywords: e-government, portal, best practices, quality model, ISO, standard, ISO 25010, ISO 9126

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16725 Description of Decision Inconsistency in Intertemporal Choices and Representation of Impatience as a Reflection of Irrationality: Consequences in the Field of Personalized Behavioral Finance

Authors: Roberta Martino, Viviana Ventre

Abstract:

Empirical evidence has, over time, confirmed that the behavior of individuals is inconsistent with the descriptions provided by the Discounted Utility Model, an essential reference for calculating the utility of intertemporal prospects. The model assumes that individuals calculate the utility of intertemporal prospectuses by adding up the values of all outcomes obtained by multiplying the cardinal utility of the outcome by the discount function estimated at the time the outcome is received. The trend of the discount function is crucial for the preferences of the decision maker because it represents the perception of the future, and its trend causes temporally consistent or temporally inconsistent preferences. In particular, because different formulations of the discount function lead to various conclusions in predicting choice, the descriptive ability of models with a hyperbolic trend is greater than linear or exponential models. Suboptimal choices from any time point of view are the consequence of this mechanism, the psychological factors of which are encapsulated in the discount rate trend. In addition, analyzing the decision-making process from a psychological perspective, there is an equivalence between the selection of dominated prospects and a degree of impatience that decreases over time. The first part of the paper describes and investigates the anomalies of the discounted utility model by relating the cognitive distortions of the decision-maker to the emotional factors that are generated during the evaluation and selection of alternatives. Specifically, by studying the degree to which impatience decreases, it’s possible to quantify how the psychological and emotional mechanisms of the decision-maker result in a lack of decision persistence. In addition, this description presents inconsistency as the consequence of an inconsistent attitude towards time-delayed choices. The second part of the paper presents an experimental phase in which we show the relationship between inconsistency and impatience in different contexts. Analysis of the degree to which impatience decreases confirms the influence of the decision maker's emotional impulses for each anomaly in the utility model discussed in the first part of the paper. This work provides an application in the field of personalized behavioral finance. Indeed, the numerous behavioral diversities, evident even in the degrees of decrease in impatience in the experimental phase, support the idea that optimal strategies may not satisfy individuals in the same way. With the aim of homogenizing the categories of investors and to provide a personalized approach to advice, the results proven in the experimental phase are used in a complementary way with the information in the field of behavioral finance to implement the Analytical Hierarchy Process model in intertemporal choices, useful for strategic personalization. In the construction of the Analytic Hierarchy Process, the degree of decrease in impatience is understood as reflecting irrationality in decision-making and is therefore used for the construction of weights between anomalies and behavioral traits.

Keywords: analytic hierarchy process, behavioral finance, financial anomalies, impatience, time inconsistency

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